{"id":"W3034425032","doi":"10.1126/science.abc5902","title":"Potent neutralizing antibodies from COVID-19 patients define multiple targets of vulnerability","year":2020,"lang":"en","type":"article","venue":"Science","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":1349,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Universiteit van Amsterdam; Bill and Melinda Gates Foundation","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Virology; Antibody; Vulnerability (computing); Neutralizing antibody; Betacoronavirus; Coronavirus Infections; Chemistry; Computational biology; Biology; Immunology; Medicine; Computer science; Computer security; Outbreak; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001536425,0.0003110846,0.0002804697,0.0002108929,0.0001530264,0.0003640297,0.000147234,0.0004066981,0.001775544],"category_scores_gemma":[0.0003999898,0.0001106186,0.0001494685,0.00009478637,0.000158347,0.0001708671,0.0002964657,0.0004205201,0.0002771576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002151124,"about_ca_system_score_gemma":0.00008064654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003528693,"about_ca_topic_score_gemma":0.0003555676,"domain_scores_codex":[0.9998871,0.00002020685,0.00001155254,0.00002072783,0.0000196619,0.00004075672],"domain_scores_gemma":[0.9998775,0.00004240592,0.00002114514,0.000008097651,0.00002110142,0.00002987712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006474279,0.0001978332,0.08326449,0.00008673524,0.00004941083,0.002771699,0.0004239207,0.0002691763,0.8829679,0.0007357117,0.0008258575,0.02775992],"study_design_scores_gemma":[0.00038547,0.006076426,0.639998,0.00007905089,0.0002009884,0.04092975,0.0008866644,0.003474407,0.2848873,0.001489121,0.02155197,0.00004074854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961436,0.0007882499,0.0007085227,0.0001118519,0.00001178025,0.00003159534,0.00007073853,0.00002055031,0.002113099],"genre_scores_gemma":[0.9985381,0.0001907813,0.0004492352,0.0001986932,0.00001316492,0.00001383598,0.0001769158,0.000005023921,0.0004142817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001775544,"threshold_uncertainty_score":0.005939722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08415653515182411,"score_gpt":0.370397834797049,"score_spread":0.2862412996452249,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}